This is part three in our five part series on the essential capabilities of the competitive data-driven enterprise.

Most business analysts will reach for their favorite data visualization tool when it comes time to perform driver and correlation analysis when in search of a cause. While this technology is essential for communicating with data, and excellent at identifying new opportunities (i.e. visualizing gaps or data non-relationships), it is limited in its ability to produce reliable, accurate and conclusive results. This is mostly due to our own human limitations when visually processing more than two dimensions of analysis at a time (e.g. revenue over time by product line). Read more

If your organization is seeking to better manage its information as a corporate asset that is to be valued and capitalized, you’re likely focused on implementing programs that will catalyze measurable business results from mountains of business information that may be the product of the last decade or more of digital transformation initiatives. Read more

It seems like data and analytics is on the top of everyone’s agenda these days. If you are accountable for providing any type of reporting, business analytics, or predictive analytics, then you are aware of the demands being placed on your time, data, and systems. If you are an executive, you are probably asking questions about your business and waiting for answers and insights. Read more

For players in the biopharmaceutical space, it is becoming increasingly clear that advanced analytics can be of enormous assistance in solving many of the unique challenges the industry faces. To understand the extent of the impact that advanced analytics can make, it’s first necessary to examine how healthcare in the US has undergone a major transformation over the past decade.

First, there’s the presence of managed care. It puts pressure on pharmaceutical companies to provide stronger evidence of efficacy and safety, reduce costs of drug development and healthcare in general, and provide personalized care by targeting patient groups that are most likely to benefit from treatments and least likely to suffer adverse events. Read more

Many of you have heard buzzwords such as “data science,” “big data,” or the “Internet of Things” before. You’re able to piece together that these fields relate to each other and deal with analyzing data in some way, but maybe you’re not so sure what these terms really mean. That’s what I’m here to help with.  As a newer member of the data science field, I developed this short data science guide based on my experiences and perspectives in an effort to help those who are just starting out. Read more

Policing in the United States and around the world is rapidly changing.  Just as there have been paradigm shifts in law enforcement procedures in the past, we are now on the brink of another transformation of how communities are policed.  Current national narratives and recent events are motivating these changes, and like it or not, a new era of law enforcement is upon us.  One of the main solutions that helps law enforcement adapt to this change is adopting a sound data driven policing strategy. Read more

For the second year in a row, Ironside has been named one of IBM’s Beacon Award finalists, this time in the category of Outstanding IBM Analytics Line-of-Business Solution. This recognition comes in honor of the compelling results that our IronShield predictive policing platform has generated.

About IronShield

IronShield Ironside predictive policing logo

IronShield provides turnkey predictive hot spots policing and analytics for law enforcement. It enables data-driven, evidence-based policing that stops crime before it happens and is customizable to the environment in which it’s implemented, going beyond its initial hot spots module to target each community’s needs. Our CEO Tim Kreytak recently highlighted the impact IronShield has had in Manchester, NH helping the city’s police department combat the heroin crisis. Read more

Suppose you’re trying to build a model to predict respondents, and in your data set, about 3% of the population will respond (target = 1). Without applying any specific analysis techniques, your prediction results will likely be that every record is predicted as a non responder (predicted target = 0), making the prediction result insufficiently informative. This is due to the nature of this kind of information, which we call highly imbalanced data. Read more

Do you ever wonder how Netflix makes recommendations for you? Or how the drug store decides which coupons to offer you when you make a purchase? Behind the scenes they have a data scientist conducting what is called market basket analysis, which searches through vast amounts of purchase history information to find patterns in people’s purchases, web searches, or Netflix viewing preferences. The data mining technique used for market basket analysis is called Association Rules (AR). This is the actual algorithm designed to detect probabilistic if- then statements, such as “If you watched Breaking Bad and House of Cards, then you are also likely to enjoy Mad Men.” Read more

Law enforcement is a place where data science and predictive analytics have the chance to truly change lives. These strategies and technologies can make a huge difference in crime prevention and public safety efforts, improving people’s wellbeing in communities of all sizes. The Manchester, NH Police Department wanted to make this kind of impact in their city, and chose to implement Ironside’s Predictive Policing platform to achieve their crime reduction goals. Read more